Change detection for target detection and classification in video sequences

Abstract

Describes a family of adaptive change detectors for detecting and segmenting moving objects in video scenes. These change detectors employ several techniques to allow them to adjust to changing image conditions. One of these is a dynamic reference frame which allows the system to adapt to changing backgrounds and produces an unambiguous target silhouette for classification. Another is a scheme to estimate system noise and adjust detection thresholds accordingly to satisfy a chosen performance criterion. Finally, adaptive normalization is used to maintain constant image contrast.